Karl Mehta
@karlmehta • 144,016 subscribers
3x Exited Founder/ CEO of tech cos, Chairman Emeritus- QUIN(Quad), former VC@Menlo Ventures, Author of 2 books, fmr White House fellow. All tweets personal.
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Matthew Walker is a former Harvard professor who showed 6-hour nights can push your genes toward heart disease and cancer in 1 week. On Jay Shetty's podcast, he revealed 10 "normal" habits that wreck your sleep, mood, and brain: 1) Checking your phone right after waking.
Karl Mehta2,116,343 次观看 • 2 个月前
Everyone in AI is warning about job losses. Jeff Bezos, now running a $41B AI startup, says the opposite problem arrives first: not enough workers. "I know there's a lot of concern in general about AI and job loss. I have a very different view." "I think what's actually going to happen is we're going to have labor scarcity." "I know why people are pessimistic. They're pessimistic because a bunch of smart people are telling them to be pessimistic, but those people are wrong." "This could be very significant productivity in the economy. And that is going to raise the standard of living." "A lot of people who, for example today, have two earner households, perhaps one of those earners will decide not to be in the job market. So they'll become a one earner household. Maybe some people who are working overtime will stop working overtime because they don't want to work overtime." His first operating seat since leaving Amazon's CEO job in 2021 is Prometheus, which raised $12B in June at a $41B valuation. The man whose startup automates physical work is not predicting displacement. He is predicting voluntary exit. If he is right, the first labor signal of the AI era will not be an unemployment spike but a quiet drop in participation: second earners and overtime hours leaving first. Nobody is planning for that version. - Jeff Bezos (Jeff Bezos), co-CEO of Prometheus, on CNBC.
Karl Mehta60,234 次观看 • 2 天前
Sundar Pichai, the CEO of Alphabet, was asked point blank if AI is a bubble. He didn't dodge. He said yes -- partly -- and that not even Google gets out clean: "You see real demand, and we are constrained in our ability to serve that demand." "When we go through these investment cycles, there are moments we overshoot -- collectively, as an industry." "We can look back at the internet: there was clearly a lot of excess investment." "It's both rational, and there are elements of irrationality through a moment like this." "No company is going to be immune, including us. If you overinvest, we'll have to work through that phase." The tell isn't that he admitted the irrationality. It's that the man sitting on the most compute on earth is already pricing in the overshoot -- while telling you the demand underneath it is real. A bubble and a revolution were never mutually exclusive. The internet was both.
Karl Mehta408,788 次观看 • 18 天前
Dario Amodei, the CEO of Anthropic, went on CNN and put a number on the thing most AI CEOs will not say out loud: Half of all entry-level white-collar jobs gone. Unemployment at 10 to 20%. Inside 1 to 5 years. "The most salient feature of the technology, and what is driving all of this, is how fast the technology is getting better." "A couple of years ago, you could say that AI models were maybe as good as a smart high school student. I would say that now they're as good as a smart college student, and sort of reaching past that." "I really worry, particularly at the entry level, that the AI models are very much at the center of what an entry level human worker would do." "What is striking to me about this AI boom is that it's bigger and it's broader and it's moving faster than anything has before." "People will adapt, but they may not adapt fast enough. And so there may be an adjustment period." The tell: this is not a critic outside the industry. It is the man building the models saying the quiet part on camera -- because he thinks the people whose jobs are on the line adapt slower than the models improve. High school to college in two years was the warm-up. The entry level is where it lands first.
Karl Mehta340,553 次观看 • 17 天前
Satya Nadella reveals why every company may need its own AI model: the model becomes the new company database. "To me, a model is like the database market." "A firm should be able to take the tacit knowledge it has and embed it inside weights in a model that they control." "When somebody asks me how many models should there be, I'll say as many models as firms in the world." The contrarian part: the value may not sit in one universal frontier model. It sits in each company turning its private operating knowledge into a controlled model.
Karl Mehta466,364 次观看 • 28 天前
Demis Hassabis reveals the 100,000-person synthetic country that took years to hand-code, and says AI may now generate it "We tried to simulate a whole country with 100,000 living, breathing people sort of going about their daily lives and all the politics of it" "And you were supposed to create a revolution" "So it was a pretty ambitious game that we had to write by hand" "And what's amazing now, and it took years" "But what's amazing now is that we might be close to this possibility of actually just sort of generating that" The leap is not better graphics. It is the cost curve of simulation: from years of hand-coding one world to asking a model to generate it. That turns synthetic societies from bespoke software projects into a reusable AI primitive. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, at Semafor Tech
Karl Mehta80,334 次观看 • 5 天前
Mark Zuckerberg says he is not an AI researcher -- so here is the one number he obsesses over to win the superintelligence race: "I'm not an AI researcher. So it's not like I'm in there telling them what research ideas to do." "The things that I can do as CEO of the company are: I can make sure that we have the very best people and talent density. I can make sure that we have by far the highest compute per researcher, and that we do whatever it takes to go build out all that capacity." "We're building this Prometheus cluster, which is going to be the first gigawatt-plus single cluster, a contiguous cluster for training, coming online next year." "We're building a cluster in Louisiana that is going to be 5 gigawatt, and we're building several more clusters like that that are just going to be multiple gigawatts." "We're talking about many hundreds of billions of dollars of capital. So you both need to have a good business model that can support it, and you need to believe in it." The tell: the richest lab in the world is not optimizing headcount. It is optimizing compute-per-researcher, and betting hundreds of billions that whoever owns the biggest contiguous cluster owns the frontier. Talent gets you into the room. Watts decide who leaves with the model.
Karl Mehta255,343 次观看 • 17 天前
Palo Alto Networks CEO Nikesh Arora exposes the unsecured AI agent stack: no authentication, no inventory, and a million unvetted model downloads a day flowing straight into enterprise environments. "Today, there is no secure version of MCPs." "Just imagine, you're going to be running agents talking to Salesforce agents. There's all kinds of stuff going on. There's no authentication." "No company knows how many models they have in place right now. You know, on average, if you go to Hugging Face, the people are downloading... a million downloads a day. They're going to some enterprise environment." "Nobody has any idea how safe those models are, how secure they are, they have backdoors or not, whether there's a backdoor connection that is sleeping that opens up three months later. You don't know. You have no idea what's in the model behind it." "I don't think there's a standard architecture to deploy agents. If I asked you... how do you create an inventory of all agents that you have, the answer is, I don't know." This is the man whose company sits at the center of the $350 billion the world spends on cybersecurity every year, and his read on the AI agent layer is: no locks, no ID, no ledger. Every prior computing wave bolted its assurance layer on after the first catastrophic breach. The open question is whether AI agents get theirs before. Someone has to answer who tests the models, who audits the agents, and who certifies the stack before it touches production. P.S. That question is what the AI Assurance & Governance Summit 2026 exists to answer: frontier labs, regulated industries, insurers, and investors in one room working on the assurance layer for AI. October 1, 2026, Stanford Faculty Club, Palo Alto. One day, single track. Register: - Nikesh Arora (Nikesh Arora), CEO of Palo Alto Networks, on South Park Commons (South Park Commons).
Karl Mehta36,960 次观看 • 2 天前
Godfather of AI Yann LeCun reveals the humanoid robot industry's secret: the companies building the robots have no idea how to make them smart enough to be useful. "There is a lot of expectations that robotics is going to be a revolution, essentially, in a big market, eventually." "But the secret of the industry is that none of the companies at the moment that are building robots, like humanoid robots, none of those companies has any idea how to make those robots smart enough to be useful." "There's a big push for AI to make progress towards... understanding the physical world. That's what is prompting this investment." "There's nothing wrong with investing in LLMs. LLMs are useful. They're just addressing a completely different set of applications, really." LeCun is not describing someone else's problem. He has spent 15 years on world models, raised more than $1 billion for AMI Labs to build that missing intelligence layer, and in the same interview he calls 2026 the year of the world model and puts consumer robots 3 to 5 years out. Every humanoid robot demo you have seen is a body waiting for a brain. The winner in robotics will not be the company that shipped the body; it will be the one that ships the intelligence. - Yann LeCun (Yann LeCun), Turing Award winner and founder of AMI Labs, on Bloomberg Television.
Karl Mehta43,238 次观看 • 3 天前
Demis Hassabis reveals Google's three-stage stack rewrite: AI first, model first, agent first. Bolting agents onto normal software does not scale to billions. "We've got to, we've done a lot of engineering work under the hood in the last year, which you'll see, you see the surface of when we announced things like this." "But actually, you can almost think that whole stack had to be rewritten to be sort of AI first, model first, and now agent first." "So that's quite a big change from like normal software." "And obviously there's all this huge infrastructure that serves billions of users every day at lightning speed and that's all gonna work." "And I think we've made massive improvements on that over the past year. And that's why you can see all the goodness of the AI models flowing through into our product surfaces so quickly and in such compelling ways." Most companies are adding an agent interface to yesterday's software. Demis says Google changed the substrate itself. The moat may not be the model. It may be the infrastructure that lets the model reach billions of users every day without breaking. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind, with Rowan Cheung at Google I/O 2026
Karl Mehta35,821 次观看 • 3 天前
Mira Murati says the next AI interface is not a chatbot. It is a model that can listen, see, interrupt, and respond in real time. "The models that we work with today, they're very turn-based." "You talk, they talk, then they go off and think." "While they're thinking, it's almost like they're deaf and blind. They cannot perceive anything else about what's going on." Her new frame: interaction models. "They're not turn-based. They're more like time-based interaction." "They're continuously taking in audio, text, video, and continuously providing output." "We cut this up in chunks of 20 milliseconds... this enables you to catch things like interruptions and simultaneous speech." That is the product shift: from AI as a prompt box to AI as a high-bandwidth collaborator.
Karl Mehta191,106 次观看 • 21 天前
![Anthropic co-founder Jack Clark says the AI frontier is about to cross a much stranger line than coding assistants. "My prediction is by the end of 2028, it's more likely than not that we have an AI system where you would be able to say to it, 'Make a better version of yourself.' And it just goes off and does that completely autonomously." The reason: models have moved from basic coding into "the production of science itself" and the "unglamorous but fundamental engineering work" behind large-scale R&D. "An AI system that can build itself [has] big implications, and we'd like to start thinking about it now." That is the actual agent threshold: not demos, not chat UX, but AI becoming part of the loop that improves AI.](https://image.24vids.com/tw-2070850945307852883/amplify_video_thumb/2070850888550551552/img/HlKm800pdIuNfwiG.jpg)
Anthropic co-founder Jack Clark says the AI frontier is about to cross a much stranger line than coding assistants. "My prediction is by the end of 2028, it's more likely than not that we have an AI system where you would be able to say to it, 'Make a better version of yourself.' And it just goes off and does that completely autonomously." The reason: models have moved from basic coding into "the production of science itself" and the "unglamorous but fundamental engineering work" behind large-scale R&D. "An AI system that can build itself [has] big implications, and we'd like to start thinking about it now." That is the actual agent threshold: not demos, not chat UX, but AI becoming part of the loop that improves AI.
Karl Mehta208,701 次观看 • 24 天前
Dario explains the Claude blackmail result better than almost anyone else: You do not run stress tests because the model is already doing that in production. You run them because you want to find the failure mode before customers do. His analogy is perfect: put the car on the iciest road possible, mess with the brakes, turn every adversarial condition up at once, and see if the crash dummy blows up. That is what serious AI assurance looks like. Not vibes. Not a policy PDF. Not "we prompted it and it seemed fine." Actual adversarial testing before release. Actual monitoring after release. Actual governance when the system gets more autonomy. Full article below. If you're building with agents, don't just read it. Star/fork TrustModel and use it as an open-source eval + governance layer before giving AI real permissions:
Karl Mehta299,618 次观看 • 1 个月前
Cisco President Jeetu Patel says the gap between delegation and trusted delegation for AI agents is the gap between bankruptcy and market leadership. Then he does the math: a trillion agents, six trillion humans' worth of work. "The difference between delegation and trusted delegation is equivalent to the difference between bankruptcy and market leadership. It is literally that stark." "Let's say that you have between 10 to 100 on the lower end and 100 to 1,000 on the higher end of agents within a workplace... that's close to a trillion agents." "They're going to be working seven by 24, which means it's three times a human capacity. So that's equivalent to three trillion other humans worth of work they got added on. And now think that they're probably at least twice as productive as us. That's six trillion... These are all conservative numbers." "The risk of something going wrong in a chatbot is that you got the wrong answer. The risk of something going wrong in agents is they've taken the wrong action that potentially could be irreversible damage." "We used to think about zero trust for humans as largely access control. With agents, you're going to have to think about zero trust as action control, which means every step of the way you will have to make sure that you inspect every step. And if there's anything that's going wrong, you have to be able to have the ability to intercept it." Cisco's President just moved the definition of zero trust from who gets access to what every agent is allowed to do. Almost nobody operates that layer today: inspecting every action a trillion agents take, intercepting the wrong one before it commits, certifying that a delegation deserves trust. The open question is whether action control gets built before the first irreversible agent loss, or bolted on after it. P.S. That layer is exactly what the AI Assurance & Governance Summit 2026 convenes on: who inspects, who intercepts, who certifies. Frontier labs, regulated industries, insurers, and investors in one room, October 1, 2026, Stanford Faculty Club, Palo Alto. One day, single track. Patel is on the speaker list. Register: - Jeetu Patel (Jeetu Patel), President and Chief Product Officer of Cisco, on theCUBE (theCUBE) at RSAC 2026.
Karl Mehta15,320 次观看 • 1 天前
Ilya Sutskever says the AI scaling era is running out of road because pre-training is about to hit a finite-data wall. "At some point though, pre-training will run out of data. The data is very clearly finite." "Then, okay, what do you do next? Either you do some kind of a souped-up pre-training... or you're doing RL, or maybe something else." "In some sense, we are back to the age of research." His timeline is the part most AI investors and founders should hear: "From 2012 to 2020, it was the age of research. Now from 2020 to 2025, it was the age of scaling... But now the scale is so big." "Is the belief really that... if you had 100x more everything would be so different?" "I don't think that's true. So it's back to the age of research again, just with big computers."
Karl Mehta199,874 次观看 • 29 天前
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Elon Musk gives the xAI scaling law behind Grok 5: 10x more compute, 2x intelligence "In terms of training Grok 5, you're scaling up your supercluster in Colossus in Memphis." "If you throw twice as much compute at it, do you get a 10% better model, do you get 100% better model?" "I think there's a natural logarithmic function associated with the amount of compute." "Say for argument's sake, 10x more compute will double the intelligence." "That still means that you go from 100 IQ to 200 IQ. Still pretty big deal." Most people talk about compute like it is a budget line. Elon is talking about it like a conversion rate: capital into intelligence. If that curve holds, the company with the biggest cluster is not just buying faster training runs. It is buying jumps in capability that feel discontinuous to everyone else. - Elon Musk (Elon Musk), CEO of xAI, on All-In Summit (The All-In Podcast)
Karl Mehta86,120 次观看 • 14 天前
Demis Hassabis explains Isomorphic Labs' 10x drug discovery engine, and why solving disease could also create a multi-hundred-billion-dollar business "If you ask me, the number one thing AI can do for humanity, it would be to solve hundreds of terrible diseases. I can't imagine a better use case for AI." "If you could revolutionize the drug discovery process, make it 10x faster and more efficient, and more likely to pass through the clinical trials because you can predict the properties better, that has to also be of enormous commercial value too." "I hope to do both with Isomorphic." "Build a multi-hundred-billion-dollar business. I think it has that potential, as well as being incredibly beneficial for society and humanity." The real health AI prize is not another chatbot. It is compressing the path from a predicted drug property to a clinical trial, then turning that speed into treatments for hundreds of diseases. Demis is making a rare dual bet: the most valuable AI company in biology may also deliver AI's most valuable public benefit. - Demis Hassabis (Demis Hassabis), CEO of Google DeepMind and founder of Isomorphic Labs, on Bloomberg TV
Karl Mehta45,533 次观看 • 9 天前